Introduction

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Introduction

Scope/context : In the Presentation Dataset Due to The Great Resignation phenomenon in the USA which describe elevated rate of workers quitting their job starting in the spring of 2021 , consequently to the covid crisis and the paradigm shift that have operated with the new work market reality and its new approach (remote work , ) , our enterprise search to understand and to anticipate why employee would and will quit their job , considering the internal parameters and try submitting again.

Variables

Number of project : describe how many projects did every employee endorse during his working sessions

Average_monthly_hours: average of hours spend at working

Time_spend_in company: how many years did the employee spent in the company

Satisfaction level: how much the employee is satisfied of his/her job

Left: express if the employee had or hadn’t left the job

promotion_last_5years: show if the employee got a promotion in the last 5 years

Department: show in which department the employee is affected/belong

Salary: Show the level of the salary for each employee

Work_accident: Show if the employee got a work accident before

Last evaluation: show the last evaluation that the employee got from the HR department

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Scoop Of context

Exploratory analysis

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Plot 1

Plot 2

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Plot 3

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Plot 4

Plot 5

Correlation Matrix

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Matrix

Advanced Exploratory Analysis

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Chart 1

Chart 2

Chart 3 MCA

Unsupervised Clustering

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CAH

Kmeans

Supervised Learning

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Logit Model


Call:
glm(formula = data_logit$salary ~ ., family = binomial, data = data_logit, 
    maxit = 100)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-1.0001  -0.4558  -0.4244  -0.2200   2.8025  

Coefficients:
                       Estimate Std. Error z value Pr(>|z|)    
(Intercept)            -2.19382    0.03526 -62.224  < 2e-16 ***
satisfaction_level     -0.05302    0.03396  -1.561   0.1185    
last_evaluation        -0.07555    0.03204  -2.358   0.0184 *  
number_project         -0.04837    0.03598  -1.344   0.1788    
average_montly_hours    0.02590    0.03278   0.790   0.4295    
time_spend_company      0.15249    0.02563   5.949  2.7e-09 ***
Work_accident1         -0.12750    0.08336  -1.530   0.1261    
left1                  -1.63858    0.12031 -13.619  < 2e-16 ***
promotion_last_5years1  0.96699    0.14025   6.895  5.4e-12 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 8542.4  on 14998  degrees of freedom
Residual deviance: 8169.4  on 14990  degrees of freedom
AIC: 8187.4

Number of Fisher Scoring iterations: 6

Decision Tree

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Decision Tree Plot